2 citations · 3 across the 4 of their papers we have counts for
4 papers
A Generalized Schwarz-type Non-overlapping Domain Decomposition Method using Physics-constrained Neural Networks
Shamsulhaq Basir, Inanc Senocak
We present a meshless Schwarz-type non-overlapping domain decomposition method based on artificial neural networks for solving forward and inverse problems involving partial differ…
An adaptive augmented Lagrangian method for training physics and equality constrained artificial neural networks
Shamsulhaq Basir, Inanc Senocak
Physics and equality constrained artificial neural networks (PECANN) are grounded in methods of constrained optimization to properly constrain the solution of partial differential…
Instabilities of longitudinal vortex rolls in katabatic Prandtl slope flows
Chengnian Xiao, Inanc Senocak
Stationary counter-rotating longitudinal vortex pairs emerge from one-dimensional Prandtl slope flows under katabatic as well as anabatic conditions due to a linear instability whe…
Characterizing and Mitigating the Difficulty in Training Physics-informed Artificial Neural Networks under Pointwise Constraints
Shamsulhaq Basir, Inanc Senocak
Neural networks can be used to learn the solution of partial differential equations (PDEs) on arbitrary domains without requiring a computational mesh. Common approaches integrate…